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Machine Learning: ECML 2003

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Cover of 'Machine Learning: ECML 2003'

Table of Contents

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    Book Overview
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    Chapter 1 From Knowledge-Based to Skill-Based Systems: Sailing as a Machine Learning Challenge
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    Chapter 2 Two-Eyed Algorithms and Problems
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    Chapter 3 Next Generation Data Mining Tools: Power Laws and Self-similarity for Graphs, Streams and Traditional Data
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    Chapter 4 Taking Causality Seriously: Propensity Score Methodology Applied to Estimate the Effects of Marketing Interventions
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    Chapter 5 Support Vector Machines with Example Dependent Costs
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    Chapter 6 Abalearn: A Risk-Sensitive Approach to Self-play Learning in Abalone
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    Chapter 7 Life Cycle Modeling of News Events Using Aging Theory
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    Chapter 8 Unambiguous Automata Inference by Means of State-Merging Methods
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    Chapter 9 Could Active Perception Aid Navigation of Partially Observable Grid Worlds?
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    Chapter 10 Combined Optimization of Feature Selection and Algorithm Parameters in Machine Learning of Language
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    Chapter 11 Iteratively Extending Time Horizon Reinforcement Learning
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    Chapter 12 Volume under the ROC Surface for Multi-class Problems
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    Chapter 13 Improving the AUC of Probabilistic Estimation Trees
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    Chapter 14 Scaled CGEM: A Fast Accelerated EM
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    Chapter 15 Pairwise Preference Learning and Ranking
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    Chapter 16 A New Way to Introduce Knowledge into Reinforcement Learning
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    Chapter 17 Improvement of the State Merging Rule on Noisy Data in Probabilistic Grammatical Inference
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    Chapter 18 COllective INtelligence with Sequences of Actions
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    Chapter 19 Rademacher Penalization over Decision Tree Prunings
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    Chapter 20 Learning Rules to Improve a Machine Translation System
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    Chapter 21 Optimising Performance of Competing Search Engines in Heterogeneous Web Environments
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    Chapter 22 Robust k -DNF Learning via Inductive Belief Merging
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    Chapter 23 Logistic Model Trees
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    Chapter 24 Color Image Segmentation: Kernel Do the Feature Space
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    Chapter 25 Evaluation of Topographic Clustering and Its Kernelization
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    Chapter 26 A New Pairwise Ensemble Approach for Text Classification
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    Chapter 27 Self-evaluated Learning Agent in Multiple State Games
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    Chapter 28 Classification Approach towards Ranking and Sorting Problems
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    Chapter 29 Using MDP Characteristics to Guide Exploration in Reinforcement Learning
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    Chapter 30 Experiments with Cost-Sensitive Feature Evaluation
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    Chapter 31 A Markov Network Based Factorized Distribution Algorithm for Optimization
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    Chapter 32 On Boosting Improvement: Error Reduction and Convergence Speed-Up
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    Chapter 33 Improving SVM Text Classification Performance through Threshold Adjustment
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    Chapter 34 Backoff Parameter Estimation for the DOP Model
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    Chapter 35 Improving Numerical Prediction with Qualitative Constraints
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    Chapter 36 A Generative Model for Semantic Role Labeling
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    Chapter 37 Optimizing Local Probability Models for Statistical Parsing
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    Chapter 38 Extended Replicator Dynamics as a Key to Reinforcement Learning in Multi-agent Systems
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    Chapter 39 Visualizations for Assessing Convergence and Mixing of MCMC
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    Chapter 40 A Decomposition of Classes via Clustering to Explain and Improve Naive Bayes
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    Chapter 41 Improving Rocchio with Weakly Supervised Clustering
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    Chapter 42 A Two-Level Learning Method for Generalized Multi-instance Problems
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    Chapter 43 Clustering in Knowledge Embedded Space
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    Chapter 44 Ensembles of Multi-instance Learners
Attention for Chapter 19: Rademacher Penalization over Decision Tree Prunings
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Chapter title
Rademacher Penalization over Decision Tree Prunings
Chapter number 19
Book title
Machine Learning: ECML 2003
Published by
Springer, Berlin, Heidelberg, September 2003
DOI 10.1007/978-3-540-39857-8_19
Book ISBNs
978-3-54-020121-2, 978-3-54-039857-8
Authors

Matti Kääriäinen, Tapio Elomaa, Kääriäinen, Matti, Elomaa, Tapio

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 50%
Researcher 1 50%
Readers by discipline Count As %
Chemical Engineering 1 50%
Unknown 1 50%